code: def load_model(
      args,
      n_entities,
      n_relations,
      ent_feat_dim,
      rel_feat_dim,
      ckpt=None,
  ):
      model = KEModel(
          args,
          args.model_name,
          n_entities,
          n_relations,
          args.hidden_dim,
          args.gamma,
          double_entity_emb=args.double_ent,
          double_relation_emb=args.double_rel,
          ent_feat_dim=ent_feat_dim,
          rel_feat_dim=rel_feat_dim,
      )
      if ckpt is not None:
          assert (
              False
          ), "We do not support loading model emb for genernal Embedding"
      return model
  
imports: import torch.multiprocessing
  from torch.utils.data import DataLoader
  import torch.optim
  import torch
  from distutils.version import LooseVersion
  from .models.pytorch.tensor_models import thread_wrapped_func
  from .models import KEModel
  from .utils import save_model, get_compatible_batch_size
  import os
  import logging
  import time
  from functools import wraps
  import dgl
  from dgl.contrib import KVClient
  import dgl.backend
  from .dataloader import EvalDataset
  from .dataloader import get_dataset
  import pdb
  from collections import defaultdict
  from ogb.lsc import WikiKG90MDataset, WikiKG90MEvaluator
  from tqdm.auto import tqdm
  import pickle
  from math import ceil
label_desc: Use image node_id 1 for calling a global function with example usage: load_model(args, n_entities, n_relations, ent_feat_dim, rel_feat_dim, ckpt) and returns: model